string c_base_type = attr_.base_type();
  if (attr_.base_type() == "type") {
    c_base_type = "DataType";
  } else if (attr_.base_type() == "shape") {
    c_base_type = "const PartialTensorShape";
  }

  // ... and wrap in a Span<> if it's a list.
  if (attr_.is_list()) {
    return absl::Substitute("absl::Span<$0>", c_base_type);
  } else {
    return c_base_type;
  }

  return attr_.full_type();
}

      : func_(func), attr_(attr) {}

  LogicalResult RewriteFunc();

  LogicalResult VerifySignature();

 private:
  LogicalResult CreateNMSCustomOptions(func::FuncOp func, DictionaryAttr attrs,
                                       std::string& custom_option_buffer);

  LogicalResult AddIntAttr(func::FuncOp func, DictionaryAttr attrs,

#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

class AttrView {
 public:
  explicit AttrView(AttrSpec attr) : attr_(attr) {}

  string VariableName() const;
  string VariableType() const;
  string AttrNameString() const;
  string VariableStrLen() const;
  string VariableSpanData() const;
  string VariableSpanLen() const;

 public:
  explicit ConvertMaxUnpoolingFunc(func::FuncOp func, mlir::TF::FuncAttr attr)
      : func_(func), attr_(attr) {}

  LogicalResult RewriteFunc();

  LogicalResult VerifySignature();

 private:
  LogicalResult CreateCustomOptions(std::string& custom_option_buffer);

  func::FuncOp func_;
  mlir::TF::FuncAttr attr_;
};

// Fuse DenseImageWarp ops annotated by tf.function to a TFLite custom op.

    control_deps_ = std::move(control_deps);
  }

  void set_attr(AttrKeyValuePair attr) {
    DCHECK(IsEmpty());
    attr_ = std::move(attr);
  }

  bool IsEmpty() const {
    return !name().has_value() && !op().has_value() && !inputs().has_value() &&
           !control_deps().has_value() && !attr().has_value();
  }

 private:
  std::optional<string> name_;
  std::optional<string> op_;

  }

  auto attrs = attr_.getAttrs();

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "pool_size", 2))) {
    return failure();
  }

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "strides", 2))) {
    return failure();
  }

  // Retrieves padding.
  auto padding = mlir::dyn_cast_or_null<StringAttr>(attrs.get("padding"));
  if (!padding) {

  }

  auto attrs = attr_.getAttrs();
  if (failed(HasIntAttr(func_, attrs, "max_detections")) ||
      failed(HasIntAttr(func_, attrs, "max_classes_per_detection")) ||
      failed(HasIntAttr(func_, attrs, "num_classes")) ||
      failed(HasFloatAttr(func_, attrs, "nms_score_threshold")) ||
      failed(HasFloatAttr(func_, attrs, "nms_iou_threshold")) ||

     * bitset by bitwise ORing the <tt>ATTR_*</tt> constants. Setting the
     * value returned by <tt>getAttributes</tt> will result in both files
     * having the same attributes.
     * 
     * @param attrs
     *            attribute flags
     * 
     * @throws CIFSException
     */
    void setAttributes ( int attrs ) throws CIFSException;


    /**

		$2 ~ /^(TASKSTATS|TS)_/ ||
		$2 ~ /^CGROUPSTATS_/ ||
		$2 ~ /^GENL_/ ||
		$2 ~ /^STATX_/ ||
		$2 ~ /^RENAME/ ||
		$2 ~ /^UBI_IOC[A-Z]/ ||
		$2 ~ /^UTIME_/ ||
		$2 ~ /^XATTR_(CREATE|REPLACE|NO(DEFAULT|FOLLOW|SECURITY)|SHOWCOMPRESSION)/ ||
		$2 ~ /^ATTR_(BIT_MAP_COUNT|(CMN|VOL|FILE)_)/ ||
		$2 ~ /^FSOPT_/ ||
		$2 ~ /^WDIO[CFS]_/ ||
		$2 ~ /^NFN/ ||
		$2 !~ /^NFT_META_IIFTYPE/ &&
		$2 ~ /^NFT_/ ||
		$2 ~ /^NF_NAT_/ ||

    }

/**
 * Return the attributes of this file. Attributes are represented as a
 * bitset that must be masked with <tt>ATTR_*</tt> constants to determine
 * if they are set or unset. The value returned is suitable for use with
 * the <tt>setAttributes()</tt> method.
 *
 * @return the <tt>ATTR_*</tt> attributes associated with this file
 * @throws SmbException
 */
    public int getAttributes() throws SmbException {